Is lovstudio-anti-wechat-ai-check safe to install?

SaferSkills independently audited lovstudio-anti-wechat-ai-check (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

skills/anti-wechat-ai-check/SKILL.md · 1 file

skills/anti-wechat-ai-check/SKILL.md4.4 KB · Markdown

name: lovstudio-anti-wechat-ai-check

category: Content Processing

tagline: "检测文章 AI 痕迹 + 人性化润色，通过微信 3.27 条款检测。"

description: >

Analyze articles for AI-generated content indicators and rewrite to pass

WeChat's 3.27 non-human automated content creation detection. Checks for

template phrases, transition word density, sentence uniformity, paragraph

pattern repetition, and other signals that WeChat uses to flag AI content.

Outputs a risk report and an optional humanized rewrite. Use when the user

wants to check if an article looks AI-generated, make an article more

human-like, bypass WeChat AI detection, or humanize AI-written content.

Also trigger when the user mentions "去AI痕迹", "人性化润色", "微信AI检测",

"anti-ai-check", "humanize article", "公众号发文检查".

license: MIT

compatibility: >

Requires Python 3.8+ (stdlib only, no external dependencies).

Cross-platform: macOS, Windows, Linux.

metadata:

author: lovstudio

version: "1.0.1"

tags: wechat ai-detection humanize content-review

anti-wechat-ai-check — 微信公众号 AI 痕迹检测与人性化润色

检测文章中的 AI 生成痕迹（模板短语、过渡词堆砌、句式雷同等），给出风险评分和修改建议，并可输出人性化润色后的版本。基于微信公众平台运营规范 3.27 条款（非真人自动化创作行为）的检测逻辑。

When to Use

用户准备将 AI 辅助写作的文章发布到微信公众号
用户想检查一篇文章是否有明显 AI 痕迹
用户想将 AI 生成的草稿改写为更自然的人类风格

Workflow (MANDATORY)

You MUST follow these steps in order:

Step 1: Get the article

Determine the input source:

If user provides a file path → read the file
If user pastes text in the conversation → save to a temp file or use --text

Step 2: Run analysis

python skills/lovstudio-anti-wechat-ai-check/scripts/analyze.py \
  --input <path> --format json

Or with inline text:

python skills/lovstudio-anti-wechat-ai-check/scripts/analyze.py \
  --text "文章内容" --format json

Step 3: Present findings

Show the user:

Risk score (0-100) and risk level (LOW / MEDIUM / HIGH)
Template phrases found — list each one with its location
Structure issues — transition word density, paragraph uniformity, etc.
Sentence issues — length uniformity, repeated starters, excessive "的"

Step 4: Ask the user

IMPORTANT: Use `AskUserQuestion` to ask what to do next:

Option	Description
仅查看报告	用户自己修改，skill 结束
给出修改建议	列出每个问题的具体修改建议，不改原文
直接输出修改版	输出人性化润色后的完整文章

Step 5: Humanize (if requested)

When rewriting, follow these humanization rules:

#### 5a. 消除模板短语

删除或替换报告中标出的每个模板短语
"随着科技的不断发展" → 直接说具体的事（"去年 ChatGPT 发布后..."）
"综上所述" → 删掉，或换成口语化的收尾

#### 5b. 降低过渡词密度

目标：过渡词密度 < 15%
删除不必要的 "首先/其次/此外/另外"
用具体的逻辑关系替代泛化连接词

#### 5c. 打破句式均匀

刻意制造长短句交替：短句 < 15 字，长句 > 40 字
加入口语化表达、反问句、感叹句
偶尔使用不完整句或省略句

#### 5d. 打破段落均匀

有的段落只有一两句话，有的段落可以很长
避免每段都是 "论点 + 论据 + 小结" 的三段式

#### 5e. 增加人味

加入个人经历、具体案例、数字细节
使用口语化表达（"说白了"、"讲真"、"你想想"）
适当使用不规范但自然的表达
减少 "的" 字使用（目标 < 5%）

#### 5f. 保留原意

核心观点和信息不能丢失
专业术语保留，不要过度口语化
保持原文的立场和态度

Step 6: Output

Output the humanized article as markdown. If the input was a file, also offer to write the result back to a file (with -humanized suffix).

CLI Reference

Argument	Default	Description
`--input`, `-i`	—	Input file path (.md, .txt)
`--text`, `-t`	—	Inline text to analyze
`--format`, `-f`	`text`	Output format: `text` or `json`

Dependencies

No external dependencies — stdlib only.

lovstudio-anti-wechat-ai-check— agent skill

Is lovstudio-anti-wechat-ai-check safe to install?

anti-wechat-ai-check — 微信公众号 AI 痕迹检测与人性化润色

When to Use

Workflow (MANDATORY)

Step 1: Get the article

Step 2: Run analysis

Step 3: Present findings

Step 4: Ask the user

Step 5: Humanize (if requested)

Step 6: Output

CLI Reference

Dependencies

Audit the pieces. Scan the whole. Decide.